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VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces
BACKGROUND: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, h...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5301390/ https://www.ncbi.nlm.nih.gov/pubmed/28187712 http://dx.doi.org/10.1186/s12859-017-1505-3 |
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author | Ali, Raja H. Bark, Mikael Miró, Jorge Muhammad, Sayyed A. Sjöstrand, Joel Zubair, Syed M. Abbas, Raja M. Arvestad, Lars |
author_facet | Ali, Raja H. Bark, Mikael Miró, Jorge Muhammad, Sayyed A. Sjöstrand, Joel Zubair, Syed M. Abbas, Raja M. Arvestad, Lars |
author_sort | Ali, Raja H. |
collection | PubMed |
description | BACKGROUND: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical difficulties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters. RESULTS: We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines. CONCLUSIONS: VMCMC is a free software available under the New BSD License. Executable jar files, tutorial manual and source code can be downloaded from https://bitbucket.org/rhali/visualmcmc/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1505-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5301390 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53013902017-02-15 VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces Ali, Raja H. Bark, Mikael Miró, Jorge Muhammad, Sayyed A. Sjöstrand, Joel Zubair, Syed M. Abbas, Raja M. Arvestad, Lars BMC Bioinformatics Software BACKGROUND: MCMC-based methods are important for Bayesian inference of phylogeny and related parameters. Although being computationally expensive, MCMC yields estimates of posterior distributions that are useful for estimating parameter values and are easy to use in subsequent analysis. There are, however, sometimes practical difficulties with MCMC, relating to convergence assessment and determining burn-in, especially in large-scale analyses. Currently, multiple software are required to perform, e.g., convergence, mixing and interactive exploration of both continuous and tree parameters. RESULTS: We have written a software called VMCMC to simplify post-processing of MCMC traces with, for example, automatic burn-in estimation. VMCMC can also be used both as a GUI-based application, supporting interactive exploration, and as a command-line tool suitable for automated pipelines. CONCLUSIONS: VMCMC is a free software available under the New BSD License. Executable jar files, tutorial manual and source code can be downloaded from https://bitbucket.org/rhali/visualmcmc/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1505-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-10 /pmc/articles/PMC5301390/ /pubmed/28187712 http://dx.doi.org/10.1186/s12859-017-1505-3 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Ali, Raja H. Bark, Mikael Miró, Jorge Muhammad, Sayyed A. Sjöstrand, Joel Zubair, Syed M. Abbas, Raja M. Arvestad, Lars VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces |
title | VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces |
title_full | VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces |
title_fullStr | VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces |
title_full_unstemmed | VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces |
title_short | VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces |
title_sort | vmcmc: a graphical and statistical analysis tool for markov chain monte carlo traces |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5301390/ https://www.ncbi.nlm.nih.gov/pubmed/28187712 http://dx.doi.org/10.1186/s12859-017-1505-3 |
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